基于否定选择遗传算法的路径覆盖测试数据生成

路径覆盖是软件测试领域重要的测试方法之一.在搜索空间中，找到一组测试数据满足路径覆盖是一个具有挑战性的问题.因此，自动生成测试数据是软件测试的关键问题.文中提出一种基于否定选择遗传算法的路径覆盖测试数据生成方法，将否定选择策略融入遗传算法，动态优化遗传算法的种群数据，自动生成覆盖目标路径的测试数据.多个基准程序和工业程序的实验结果表明，与随机方法和遗传算法比较，文中方法能够提高路径覆盖率，减少冗余测试数据的生成.

Test Data Generation of Path Coverage Based on Negative Selection Genetic Algorithm

Path coverage is one of the most important testing methods in the field of software testing.It is a challenging problem to find a set of test data to satisfy the path coverage in the search space.Therefore,automatically generating test data is a key issue in software testing.In this paper,a generation method of test data based on the negative selection genetic algorithm is proposed.The negative selection strategy is integrated into the genetic algorithm,and the population data of the genetic algorithm is dynamically optimized,and the test data covering the target path is automatically generated.The experimental results show that compared with the random method and the genetic algorithm,the proposed method can improve the path coverage and reduce the generation of redundant test data.